class_docstr: Unit test for posterior sampling with Gaussian likelihood and Gaussian prior
class_docstr_tok: ["Unit","test","for","posterior","sampling","with","Gaussian","likelihood","and","Gaussian","prior"]
docstr: Computes Mean 
docstr_tok: ["Computes","Mean"]
code: def _compute_mean(self, samples):
      """Computes Mean"""
      return np.mean(samples)
  
file_path: dragonfly/dragonfly/distributions/unittest_posterior.py
imports: from __future__ import absolute_import
  from __future__ import division
  import unittest
  import numpy
  from .continuous import Normal
  from .model import Model
  from ..utils.base_test_class import BaseTestClass, execute_tests
label_desc: Use image node_id 3 for calling the PosteriorTestCase obj's underlying member method code with example usage: obj._compute_mean(samples) and returns: np